The coronavirus disease 2019 (COVID-19) outbreak has been associated with stress and challenges for healthcare professionals, especially for those working in the front-line of treating COVID-19 patients. This study aimed to: 1) assess changes in well-being and perceived stress symptoms of Dutch emergency department (ED) staff in the course of the first COVID-19 wave, and 2) assess and explore stressors experienced by ED staff since the COVID-19 outbreak.We conducted a cross-sectional study. An online questionnaire was administered during June–July 2020 to physicians, nurses and non-clinical staff of four EDs in the Netherlands. Well-being and stress symptoms  were scored for the periods pre, during and after the first COVID-19 wave using the World Health Organization Well-Being Index (WHO-5) and a 10-point Likert scale. Stressors were assessed and explored by rating experiences with specific situations  and in free-text narratives. Quantitative data were analyzed with descriptive statistics and generalized estimating equations (GEE). Narratives were analyzed thematically.p < 0.001) during the peak of the first wave and 3.7 points (< 0.001) after the first wave. Mean self-perceived stress symptom levels almost doubled during the peak of the first wave (≤0.005). Half of the respondents reported experiencing more moral distress in the ED since the COVID-19 outbreak. High levels of distress were primarily found in situations where the staff was unable to provide or facilitate necessary emotional support to a patient or family. Analysis of 51 free-texts revealed witnessing suffering, high work pressure, fear of contamination, inability to provide comfort and support, rapidly changing protocols regarding COVID-19 care and personal protection, and shortage of protection equipment as important stressors.In total, 192 questionnaires were returned (39% response). Compared to pre-COVID-19, the mean WHO-5 index score (range: 0–100) decreased significantly with 14.1 points COVID-19 patients during future infection waves.The online version contains supplementary material available at 10.1186/s12913-021-06555-5. On 30 January 2020, The World Health Organization declared the coronavirus disease COVID-19) as a public health emergency of international concern [9 as a puThe COVID-19 outbreak has been associated with mental problems and challenges for many people, including healthcare professionals treating COVID-19 patients in the frontline –6. ProfeThe impact of COVID-19 on healthcare professionals’ health status have been investigated in many previous studies –10. HoweWe performed a cross-sectional survey study in the period from June 18 to July 242,020. Quantitative and qualitative data were collected through an online questionnaire from clinical and non-clinical staff of four EDs  in the eastern region of the Netherlands. On February 27, 2020, the first patient with COVID-19 was hospitalized in a Dutch hospital. This date marks the start of the COVID-19 outbreak in the Netherlands [This study is reported in accordance with the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guideline. The local ethics committee CMO region Arnhem - Nijmegen approved the study (registration number: 2020–7145). The survey started with an informed consent of the study. Participation was only possible after reading the informed consent and selecting the “agree” option, otherwise the questionnaire could not be filled out.All physicians , nurses, nursing assistants and administrative staff  who worked in the ED since February 27, 2020, received a questionnaire. Eligible staff members were identified per study site by the head of the department or a senior staff member, and locally invited by e-mail to complete an online questionnaire. This email contained a standardized template consisting of general information about the study, how their personal data is stored and protected, and a link to the questionnaire. One reminder was sent 14 days after the initial invitation. In the invitation and reminder email staff members were kindly asked to fill in the questionnaire only once to avoid multiple responses from the same participant. Each participant completed the survey anonymously. Data were collected using Limesurvey – a frequently used and secured online questionnaire program – and subsequently transferred by GH to a secured database in the protected server of the Radboudumc.before the COVID-19 outbreak (February 27), during the peak of the first COVID-19 wave (February 27 to April 1) and after the first COVID-19 wave (the last 2 weeks since receiving the questionnaire). In the Netherlands, the first COVID-19 wave came to an end in the beginning of June [The questionnaire consisted of seven main sections: 1) general information on socio-demographics and occupation, 2) well-being, 3) stress symptoms, 4) moral stress; 5) experiences with stressors, 6) working climate and 7) managerial support. The data gathered on the last two sections were separately analysed in another study. General information included: gender, age, marital status, household size, caregiver tasks, professional function and hospital/study site, work experience and work-related information . Well-being was evaluated using a Dutch version of the five-item version of the World Health Organization Well-Being Index (WHO-5) which has proven to be a valid screening tool for well-being . We aske of June . The WHOStress symptoms were evaluated for the abovementioned three time periods on a Likert scale ranging from 0 (none) to 10 (very much). We asked participants to rate symptoms related to cognitive stress , emotional stress  and physical stress  . In addiLevels of distress were assessed by rating 13 items describing specific clinical situations found to generate distress among health care staff . Participants were asked to rate, on a 5-point Likert scale, how often they experienced this situation  and how much the situation would disturb them  since the COVID-19 outbreak. Five situations were derived from the Measure of Moral Distress for Healthcare Professionals (MMD-HP) . Eight sAll statistical analyses were performed using SPSS version 23.0. Descriptive statistics were used to summarize respondent’s sociodemographic and occupational characteristics, well-being, stress symptom levels, changes in moral distress, and the frequency and intensity of stressors. Frequency, percentage, mean, standard deviation (SD), median and interquartile range (IQR) scores were used according to the data type.p value <.05 was considered to be statistically significant, based on two-sided testing. Differences  in well-being and stress symptom levels were investigated across gender groups  and types of professional function  using the unpaired t-test.The raw scores on the WHO-5 items were transformed to an index score between 0 to 100, with lower scores indicating worse well-being. An index score of ≤50 indicates poor well-being and suggests further investigation into possible symptoms of depression . CronbacA mean composite distress score was calculated for each of the 13 described situations to compare levels of distress by situation and participant type. A composite distress score was calculated by multiplying frequency and intensity (0–16) with higher scores suggesting higher levels of distress. The level of distress experienced is a function of how often a situation occurs and how distressing it is when experienced . The claA total of 495 eligible persons were approached to participate. One hundred ninety-two completed questionnaires were returned, resulting in a response rate of 39%. Respondents were comparable to the total population eligible to participate when looking at the gender ratio, professional function and age. A comparison is shown in Additional file Data on the characteristics of the respondents are shown in Table p < 0.001) during the peak of the first wave and 3.7 points (p < 0.001) after the first wave. On average, respondents’ well-being improved after the first COVID-19 wave, but remained lower than before the COVID-19 outbreak. The development of respondents’ well-being in the course of the COVID-19 outbreak is shown in Fig. p < 0.01).Differences were found in the mean WHO-5 index scores before, during and after the first COVID-19 wave for all respondents combined Table . Comparep < 0.001) during the peak of the first wave, and 0.4 points (=0.005) after the first wave. Emotional stress symptoms increased significantly with 2.1 points (p < 0.001) and 0.4 points (=0.003), respectively. Physical stress symptoms increased significantly with 1.5 points (p < 0.001) and 0.4 points (< 0.001), respectively. On average, experienced stress symptoms almost doubled during the peak of the first wave. Stress symptom levels decreased after the first COVID-19 wave, but they remained higher than before the COVID-19 outbreak. Figure p = 0.01). Compared to the rest of the respondents, physicians scored significantly lower on self-perceived emotional and physical stress symptoms during the peak of the first wave (p = 0.04 and p < 0.01 respectively).Differences were also found in the mean scores on self-perceived stress symptoms Table . Compareand moderate-low on intensity, or vice versa. Highest distress scores were mostly found for nurses (eight situations) followed by nursing assistants (five situations).High levels of distress  were found on three of the thirteen situations, namely situations where respondents were: not able to facilitate a decent goodbye between patient and family members (item 4), not able to provide the necessary emotional support to a patient and family members item 5), and required to care for patients that could endanger the health of their own family (item 2). Figure , and reqRespondents described 51 stressors which were organized into six themes Table . Most naThe COVID-19 outbreak had a serious impact on the well-being and mental health of ED staff. In the peak of the first wave the staff well-being dropped to a level that is close to the threshold (≤50) indicating the need for screening for depression . CognitiThe COVID-19 outbreak also had an impact on the psychological distress of the ED staff. A large part of the ED staff (50%) experienced more moral distress since the outbreak. Our findings showed high levels of distress, both in frequency and intensity, which were primarily caused by situations where the staff was hindered in providing the clinical and emotional care they are used to provide under ‘normal’ conditions. The use of self-evident safety precautions regarding the virus and the limited options to effectively treat COVID-19 is presumably disturbing to many professionals as they are in sharp contrast with perceived standards of good care. The fear of being exposed to COVID-19 at work and taking the infection home to their family was reported as another important stressor, also known from previous studies , 30, 31.Respondents’ narratives revealed multiple factors causing psychological distress. Many of these factors are potentially amendable to managerial intervention. For example, by managers encouraging staff to ask for help when they need it and by offering various types of support  –36. HealTo our knowledge, this study is one of the first to investigate the impact of COVID-19 on the well-being and phycological distress of various types of professionals working in multiple EDs. Several limitations of the study should however be noted. First, the response rate to our questionnaire was modest at 39%. Unfortunately, web-based survey research among healthcare professionals shows substantial variation in reported response rates and rates below 20% are not uncommon . Our resThis study adds to recent literature showing that he COVID-19 pandemic takes its toll on ED staff. The question is how long the frontline remains intact with the ongoing pandemic. We hope that this study contributes to a public awareness of the impact of infection peaks on ED staff. Timely and adequate actions by ED and hospital management to limit drop-out and illness among staff resulting from psychological distress are vital to secure acute care for (non)COVID-19 patients during future infection waves.Additional file 1: Table S1. The classification of distress composite, frequency and intensity scores into low, moderate and high.Additional file 2: Table S2. Respondents compared to all eligible persons approached for study participation on gender, age and professional function.Additional file 3: Figure S1. Longitudinal modelling on mean WHO-5 index scores per professional function. Figure S2. Longitudinal modelling on mean WHO-5 index scores per gender group.Additional file 4: Figure S1. Longitudinal modelling on mean cognitive stress symptom scores per professional function. Figure S2. Longitudinal modelling on mean cognitive stress symptom scores per gender group. Figure S3. Longitudinal modelling on mean emotional stress symptom scores per professional function. Figure S4. Longitudinal modelling on mean emotional stress symptom scores per gender group. Figure S5. Longitudinal modelling on mean physical stress symptom scores per professional function. Figure S6. Longitudinal modelling on mean physical stress symptom scores per gender group.Additional file 5. Table. Composite distress score, frequency and intensity of distress on thirteen specific clinical situations, overall and by profession.Additional file 6. Figure. Mean frequency score, overall and by profession.Additional file 7. Figure. Mean intensity score, overall and by profession.


Bladder cancer is the tenth most common cancer worldwide. Valuable biomarkers in the field of diagnostic bladder cancer are urgently required.  Here, the gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA), GSE13507, GSE32894, and Mariathasan et al. Five prognostic genes were identified by the univariate, robust, and multivariate Cox's regression and were used to develop a prognosis-related model. The Kaplan–Meier survival curves and receiver operating characteristics were used to evaluate the model's effectiveness. The potential biological functions of the selected genes were analyzed using CIBERSORT and ESTIMATE algorithms. Cancer Therapeutics Response Portal (CTRP) and PRISM datasets were used to identify drugs with high sensitivity. Subsequently, using the bladder cancer (BLCA) cell lines, the role of TNFRSF14 was determined by Western blotting, cell proliferation assay, and 5-ethynyl-20-deoxyuridine assay. β-catenin-dependent pathway. TNFRSF14 is a potential protective biomarker involved in cell proliferation in BLCA.  GSDMB, CLEC2D, APOL2, TNFRSF14, and GBP2 were selected as prognostic genes in bladder cancer patients. The model's irreplaceable reliability was validated by the training and validation cohorts. CD8+ T cells were highly infiltrated in the high-TNFRSF14-expression group, and M2 macrophages were the opposite. Higher expression of TNFRSF14 was associated with higher expression levels of LCK, interferon, MHC-I, and MHC-II, while risk score was the opposite. Many compounds with higher sensitivity for treating bladder cancer patients in the low-TNFRSF14-expression group were identified, with obatoclax being a potential drug most likely to treat patients in the low-TNFRSF14-expression group. Finally, the proliferation of BLCA cell lines was increased in the TNFRSF14-reduced group, and the differential expression was identified. TNFRSF14 plays a role in bladder cancer progression through the Wnt/ We conducted a study to establish a 5-gene score model, providing reliable prediction for the outcome of bladder cancer patients and therapeutic drugs to individualize therapy. Our findings provide a signature that might help determine the optimal treatment for individual patients with bladder cancer. Bladder cancer (BLCA) is the tenth most common cancer worldwide . It is thttps://cancergenome.nih.gov/) and Gene Expression Omnibus  have provided extensive sequencing data to explore gene function, including cancer-associated genes. There are prognostically relevant multicohort validated models for many cancer types, including breast cancer [Advances in second-generation high-throughput gene sequencing and construction of genome databases of cancers such as TCGA . A total of 165 samples with overall survival time, state, clinical stage, sex, and age were obtained from GSE13507 [https://portals.broadinstitute.org/ccle/) [https://portals.broadinstitute.org/ctrp), including 481 compounds with over 835 CCLs, and the PRISM Repurposing dataset , including 1448 compounds with over 482 CCLs.The gene expression matrix and clinical data were obtained from TCGA. Data from 429 BLCA samples were used, including 18 nontumor tissue samples adjacent to the tumor and 411 tumor tissue samples. All BLCA patients included in TCGA were used as the training set. Expression levels of genes were standardized by logGSE13507  on the GGSE13507  on the Gg/ccle/) . Drug sep < 0.05 were selected using “Survdiff” commands in R language, and GraphPad Prism 8.0 was used to draw the Kaplan–Meier survival curves and receiver operating characteristic (ROC) curves of 1, 3, and 5 years to assess their correlations with outcome [We selected differentially expressed genes with median and variability of expression levels higher than 20 percent of all genes. Then, the degree of correlation between gene expression and overall survival was assessed in the training set. We used the “survival” package  in R sof outcome . Expressp < 0.05 are considered significant. Gene set enrichment analysis was used to determine different pathways enriched in the high- and low-TNFRSF14-expression group.Gene lists and proteomic studies from high-throughput sequencing were biologically interpreted using the Database for Annotation, Visualization, and Integrated Discovery , a function enrichment tool, to determine the possible biological functions of the screened genes . DAVID wp < 0.05) according to the log-rank test [To create the most stable prognostic model and minimize the degrees of freedom to reduce costs, the principle of robust likelihood-based survival analysis and AICs was applied to screen the genes selected by univariate regression analysis according to the following parameters: iteration times = 100 and max concern genes = 20 , 26. Theank test .A prognostic model was constructed with the multivariate Cox regression analysis using the five selected robust outcome-related genes. Hazard ratios were used to determine whether a gene is a cancer-promoting (ratio < 1) or cancer-inhibiting factor (ratio > 1). The risk score for each patient was calculated, and the amounts of the five prognostic factors were determined using the “pheatmap” package. The effects were evaluated by drawing the Kaplan–Meier and ROC curves in the training set, test sets, and multiple subgroups.https://cibersort.stanford.edu/) used to calculate expression levels of 22 immune cell subtypes [The Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) is an algorithm used to calculate the fractions of stromal and immune cells based on gene expression levels . We calcsubtypes . Expresshttps://cran.r-project.org) or BioConductor (http://www.bioconductor.org) in the R language (R x64 4.0.3). The Wilcoxon test was used to compare differences between two groups, and the Kruskal–Wallis test was used to compare differences between multiple groups. If p < 0.05, differences were considered statistically significant; if p < 0.01, there was a highly significant difference between the groups.All statistical analyses were performed using the R package downloaded from CRAN  targeting TNFRSF14 to reduce its expression were purchased from JTSBIO Co. (China). The si-TNFRSF14 (H) -539 (#1) sequences were as follows: sense, CCUACAUUGCCCACCUCAATT; anti-sense, UUGAGGUGGGCAAUGUAGGTT. The si-TNFRSF14 (H) -941 (#2) sequences were as follows: sense, GCUCCACAGUUGGCCUAAUTT; anti-sense, AUUAGGCCAACUGUGGAGCTT.The BLCA cell lines T24 and UMUC3 were purchased from the Chinese Academy of Sciences Cell Bank (China). T24 and UMUC3 were cultured in RPMI 1640 and DMEM (high-glucose) medium (Hyclone) containing 10% fetal bovine serum, respectively. Both cell lines were cultured at 37°C with 5% COTotal RNA was extracted using RNAiso Plus . After the manufacturer's instruction, total RNA was reverse transcribed into cDNA with PrimeScript RT Master Mix . SYBR® Premix Ex Taq™ Kit  was used to perform qRT-PCR. The Thermal Cycler Dice™ Real-Time TP800 system  was used to perform all analyses. GAPDH was used as an internal reference, and the relative expression level of a gene was calculated by the ΔΔCT method. The primer sequences are listed as follows: TNFRSF14  and GAPDH .β-catenin and cyclin D1, the membranes were incubated at 4°C overnight. After washing three times with TBS-T, the membranes were incubated with a secondary antibody for 1 hour at 37°C and then washed again. The enhanced chemiluminescence method was used to observe the protein expression, and ImageJ software was used to calculate the protein expression value.Cells were lysed in radioimmunoprecipitation assay (RIPA) buffer, protein was taken, and the concentrations were measured using a bicinchoninic acid assay kit. The proteins were separated using 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and the proteins were transferred to polyvinylidene fluoride membranes. Subsequently, the membranes were blocked using Tris-buffered saline with 1% Tween 20 (TBS-T) with 5% nonfat milk at 37°C for 1 h. After adding primary antibodies for T24- and UMUC3-treated cells were seeded in 96-well plates, and the Cell Counting Kit-8 (CCK-8) assay reagent  was added to each well following the manufacturer's instructions. An absorbance reader (Bio-Rad) was used to measure the absorbance at a wavelength of 450 nm.μl medium containing 50 μM EdU was added to each well for 3 hours. After aspirating the culture medium, 4% paraformaldehyde was added to each well to fix the cells at room temperature for 15 min. Subsequently, 0.3% Triton X-100 in phosphate-buffered saline was added to each well at room temperature for 15 min, and then the cells were incubated for 30 min with click reaction solution. Finally, Hoechst 33342 diluted in phosphate-buffered saline (1 : 1000) was added to each well at room temperature for 10 min. The proportion of EdU-positive cells was observed with a fluorescence microscope  and photographed. The percentage of EdU-positive cells was calculated using the ImageJ software .The proliferation ability of the cells was detected with the 5-ethynyl-20-deoxyuridine (EdU) assay kit . A total of 2000 cells were added to each well in a 96-well plate after transfection. After 18 h, 500 n = 165) and GSE32894 (n = 224) were used. These patient samples included RNA expression, overall survival time, survival status, clinical stage, gender, and age. We also used the cohort from Mariathasan et al. (n = 195).The expression levels and clinical data of 429 BLCA samples were acquired from TCGA, including 410 tumor samples and 19 nontumor samples. GSE13507  was randomly divided into a subtraining set with N∗(1 − p) samples and a subvalidation set with N∗p samples (p = (1/3)). A gene was fitted to the subtraining set of samples, and the parameter estimate was obtained. Then, log-likelihood with the parameter estimate and the subvalidation set were evaluated. This evaluation was performed for each gene.In the first step, the training set  were selected. The best genes were the ones most closely associated with survival selected by the robust likelihood-based approach.In the third step, Gene A was regarded as the best-selected gene in the previous step. We found the next best gene (B) by repeating the previous two steps.K models M1 = A, M2 = A + B, and MK = A + B + ⋯+K.In the fourth step, this selection was continued until there were no more samples, resulting in a series of In the final step, the best genes that were marked as (∗) were selected in the model with the smallest AIC, which was considered the most stable and sound model with the least number of degrees of freedom , as shown in Using the multivariable Cox regression analysis, a risk score model was established with the five selected robust genes to calculate the correlation between the comprehensive expression levels of the five genes and patients' outcomes . The risp < 0.0001   were used for validation to validate the model's reliability further. The survival curves indicated that the model was significant in all three cohorts, i.e., patients in the high-risk group had worse outcomes than those in the low-risk group.  Figures . The ROCThe risk score formula was also applied to calculate the risk value of each sample in the four cohorts and the obtained value of the risk score. The survival status and the expression levels of the five selected genes for each sample are shown in Figures CIBERSORT was used to calculate the expression of 22 immune cells from all BLCA samples in TCGA. All samples were divided into high- and low-TNFRSF14-expression and high- and low-APOL2-expression groups, respectively. The differences in expression levels of 22 immune cells between high- and low-expression groups were displayed in box plots. The results showed that CD8+ T cells were highly infiltrated in the high-TNFRSF14-expression group, and M2 macrophages were less highly expressed in the high-TNFRSF14-expression group. This was also the case in the high- and low-APOL2-expression groups Figures . The heaK-nearest neighbor (k-NN) imputation was used to fill in the missing AUC values. Finally, 354 compounds in the CTRP dataset and 1285 PRISM datasets were used for subsequent analysis. Subsequently, the pRRophetic package was applied to predict the effect of candidate drugs applied to clinical patients, and the corresponding estimated AUC values were obtained. AUC values are negatively related to the sensitivity of the drug.There are gene expression and drug response data from hundreds of cell lines for CCLs in the CTRP and PRISM datasets, which can be used as a test set for drug response. Both datasets had a total of 1770 compounds, and we excluded samples and cell lines with more than 20% NA in hematopoietic and lymphoid tissues. 2FC < −0.10). Next, the AUC values and TNFRSF14 expression were subjected to Spearman's correlation analysis to select compounds with positive correlation (Spearman's r > 0.20 for CTRP or 0.30 for PRISM). Finally, 12 compounds in CTRP  and 14 compounds in PRISM  were screened out. All these compounds had lower estimated AUC values in the TNFRSF14 low-expression group and a positive correlation with TNFRSF14 expression  and low-TNFRSF14- (bottom decile) expression groups to identify compounds with lower estimated AUC values in the low-TNFRSF14-expression group  can affect tumor progression, recurrence, metastasis, and resistance to therapy , 35, andPyroptosis is a novel programmed cell death mechanism discovered in recent years . Zhou etInflammation is an essential process in the tumor microenvironment mediated by a mixture of cytokines secreted by tumors and immune cells , 44. In Apolipoprotein L2 (APOL2) belongs to the L family of lipid-binding proteins –52. The Tumor necrosis factor receptor superfamily 14 (TNFRSF14), a protein encoded by this gene which is also called HVEM, encodes members of the tumor necrosis factor (TNF) receptor superfamily and activates proinflammatory pathways . TNFRSF1Guanylate-binding protein 2 (GBP2) is a member of the GBP family. When GBP2 is absent in macrophages, there are blunted immunological responses, suggesting that it plays an essential role in the inflammatory process , 60. TheMeasurement of the degree of 22 immune cell infiltration suggested that the expression of TNFRSF14 and APOL2 is strongly correlated with CD8+ T cells and M2 macrophages. Jansen et al. suggested that BLCA patients with a high degree of infiltration of CD8+ T cells had good outcomes and strong responses to immunotherapy . In BLCAEnhancement of antitumor activity requires tumor neoantigen-specific CD8+ T cells to inhibit tumors via major histocompatibility complex- (MHC-) I  and enhaγ, secreted by CD8+ cytotoxic T lymphocytes, inhibits tumors, an essential part of antitumor immune responses [α expands CD8+ T cells on a large scale and blocks the cycle of cancer cells, thereby improving outcomes [Interferon signaling is involved in the immune surveillance mechanism of tumors . Interfeesponses . IFN-α eoutcomes . In our β-catenin-dependent pathways, and noncanonical Wnt pathways [β-catenin-dependent pathway [The Wnt signaling pathways were divided into canonical pathways, Wnt/pathways . The propathways . Cyclin  pathway , and cyc pathway .Obatoclax can be used to reduce the resistance of BLCA cells to paclitaxel , and pacAlthough the five-gene robust model established in this study predicted outcomes in BLCA, there remain some limitations of the present study. Previous investigators provided the patient data. There were also few cohorts for external validation. Furthermore, the reliability of the robust model was only analyzed at the sequencing level and was not clinically validated. Panobinostat (PAN) can increase the sensitivity of muscle-invasive BLCA cells to radiation . TreatmeIn conclusion, a reliable risk score model was established to predict outcomes in patients with BLCA and identify the screened genes' possible biological functions. CD8+ T cells and M2 macrophages were related to the expression of the selected genes. Expression levels of MHC-I, MHC-II, LCK, and interferon were associated with the expression of THFRSF14 and the risk score. Tumor purity is correlated with the expression of THFRSF14 and the risk score. Obatoclax may be a potential drug most likely used to treat patients in the low-TNFRSF14-expression group. Nevertheless, further studies are needed to validate the stability of the predictions of the established model and evaluate its practical value in clinical applications.


Ni(1−x)CuxMn2O4-Bio (NCB) NPs were studied by powder X-ray diffraction technique, scanning electron microscopy and Raman spectroscopy. XRD spectra authenticated the copper-doped nickel manganites’ formation with particle size 23–28 nm. A significant decrease in the lattice parameter confirmed the doping of copper ions into the nickel manganites. Microscopy (SEM) was used to estimate the grain size, shape and uniformity, revealing the non-uniform agglomerated polygon and plate-like microstructure. The NCB-NPs showed anticoagulant activity by enhancing the coagulation time of citrated plasma of human beings. NCB-NPs with x = 0.35 and 0.45 have increased clotting time from control 133 ± 4 s to 401 ± 7 s and 3554 ± 80 s, respectively, and others around 134 s. Additionally NCB-NPs with x = 0.35, 0.45 inhibited the platelet aggregation by 80% and 92%, while remaining inhibited with only 30%. NCB-NPs did not show hemolytic activity in RBC cells intimate its non-toxic nature. Finally, NCB-NPs were non-toxic and known to exhibit anti-blood-clotting and antiplatelet activities, which can be used in the field of biomedical applications, especially as antithrombotic agents.Copper-substituted nickel manganites Ni Magnetic substances have nano-technological applications in areas such as analytical chemistry, biosensing and nano-medicine. These magnetic nanoparticles (MNPs) are eco-friendlier and more compatible with the applications in the field of pharmacy and biomedicine ,2. MetalThe thrombotic disorder is the major cause of death in cardiovascular disorders, directly resulting from pathological thrombogenesis or thrombus-exuviation-induced vascular embolism. Hyperactivation of blood coagulation factors in the coagulation cascade triggers downstream thrombin activation and platelet aggregation. The process culminates in the formation of insoluble fibrin, along with cellular components, eventually leading to the formation of thrombus. However, the main concern of NPs is their interaction with blood components. There is a potential in the study of NPs’ interaction with the components of the blood clotting system that may be an important part of their safety profile. Blood coagulation may be a tightly regulated mechanism that plays an important role in maintaining the fluidity of the blood and in arresting bleeding during injury. Several factors alter the coagulation mechanism, leading to the unnatural formation of blood clots in arteries and veins that may contribute to cardio/cerebrovascular disorders. Anticoagulant and antiplatelet agents prevent or delay the formation of thrombi. There are many challenges in clinical usage of anticoagulant drugs, such as short half-life in the plasma, repeated administration and high cost. Anti-blood-clotting nanoparticles (NPs) can help to reduce dosage and side effects and increase efficacy. The physical and chemical properties of the NPs’ surface show various types of interactions with the proteins that may lead to changes in protein conformation, activation or inhibition of blood-coagulation factors.2O4, in which cations reside at both tetrahedral (A-sites) and octahedral (B sites) showed good NTC thermistor properties, dielectric capabilities, magnetic nature and ease of production, are promising materials for biological investigation [(1−x)CuxMn2O4 (NCB-NPs), along with their effect on plasma coagulation and platelet aggregation.Manganese-based transition-metal oxides are extensively used to control, monitor and compensate the temperature in household appliances, manufacturing units, health sector, biomedicine, aerospace, cryogenics and automotive factories . The littigation . Quite aNanotechnology has been used in multiple applications in the field of therapeutics, such as early diagnosis, imaging and medicine-delivery systems . There i2O4 (space group: Fd3m) with JCPDC card #00-084-0542. The X-ray diffraction spectra of NCB-NPs  samples are presented in a is determined by using the following equation:d is the distance between consecutive planes, and (h k l) are Miller indices of crystallographic planes. The value of lattice constant calculated ranges from 8.52 to 8.38 Å. Crystalline size, D, was determined with the help of the Debye–Scherer equation [λ is the wavelength of X radiations, β is the full width half maximum (FWHM) of diffraction peak and θ is Bragg’s angle. As XRD peaks of the synthesized sample are sharper and more intense, having a larger grain size of 3 μm, which will have higher electrical conductivity due to lower grain boundary resistance in accordance with Scherer expression. It was found from the below From the X-ray diffraction pattern, lattice parameter equation .D = 0.9The surface morphology details were obtained by analyzing the SEM images of prepared copper-doped nickel manganites, as presented in −1 are presented in 7h (Fd-3m)O, it produces five Raman-sensitive states (A1g + Eg + 3F2g) [−1. The wide peak at 646 cm−1 is attributed to A1g-sensitive states, which evolved due to symmetric expanding vibrations of Mn–O in MnO6 octahedral position. The remaining three peaks are attributed to F2g-sensitive states corresponding to Ni–O expanding vibration in both octahedral and tetrahedral positions [1g mode are inversely proportional to the lattice parameter of the spinel; even the shift in wavenumber of the Raman-active mode is only around 1%, which is evident from The Raman spectra of NCB-NPs (x = 0.15 and x = 0.35) with wavenumbers from 300 to 800 cm + 3F2g) . Figure Hemostasis is a complex physiological process that drives immediate response upon blood vessel injury. Blood coagulation follows two pathways: the contact activation tract (intrinsic pathway) and the tissue factor tract (extrinsic pathway). These tracts independently culminate at a common tract that is the conversion of prothrombin (factor II) to thrombin (factor IIa). Thrombin is a serine protease that hydrolyzed soluble fibrinogen to form insoluble fibrin monomers. Later, fibrin monomer polymerizes, along with other cellular components, to form a fibrin clot that helps to plug damaged blood vessels, arresting the bleeding ,18,19. M2 was put into the pre-cultured mixture, and the coagulation time was recorded. The plot of coagulation time and concentration of NCB-NPs is as shown in Different concentrations of NCB-NPs were pre-cultured with 0.2 mL of citrated human plasma PRP/PPP, taking the help of 20 μL of 10m MTris-HCl buffer (pH 7.4) for 1 min at 37 °C. Then 20 μL of 0.25 M CaClTo evaluate the effect of NCB-NPs in coagulated plasma, the clotting time of citrated plasma of human beings was examined by using plasma rich in platelets. NCB-NPs showed the anticoagulant effect by increasing the plasma coagulation time of PRP from control 145 to 400 s and from 145 to 3000 s for NCB-NPs with x = 0.35 and 0.45, respectively, while they showed constant plasma coagulation time of PRP around 134 s only. The highest concentration used in the two cases was confirmed to be 2 mg. There is a need to synthesize NPs, which have anticoagulant properties that can be used to coat surgical instruments. Very few studies have reported the anticoagulant and thrombolytic effects of NPs. The NCB-NPs have shown significant anticoagulant effects.The platelets play a significant role in the maintenance of hemostasis and thrombus formation. Platelets are the cellular components of blood clotting that originated from megakaryocytes in the bone marrow. Platelets consist of a peripheral zone with glycoprotein receptors; contractive microtubules; and organelles with alpha granules, dense granules and lysosomes. The activation of platelets is induced by binding of surface receptors to fibrinogen, thromboxane A2, thrombin, ADP, adrenaline, collagen and vWF . NPs genPlatelet accumulation was monitored by analyzing light transmission in a CHRONO-LOG Model 700 Aggregometer. Platelet-rich plasma (0.25 mL) was incubated with different concentrations (0–2 mg) of NCB-NPs. Then platelet accumulation was started by adding ADP (10 µM), and aggregation was observed as shown in To evaluate the effect of NCB-NPs on platelets, platelet aggregation assay was performed in a CHRONO-LOG platelet aggregometer, using PRP with ADP as agonists. The NCB-NPs with x = 0.35 and x = 0.45 inhibited the platelet aggregation to an extent of 80% and 93%, respectively, while remaining inhibited with only 30%. In the general mechanism of platelet aggregation, ADP is released from activated platelets and leads to the self-activation of other platelets, ultimately leading to platelet aggregation. Uncontrolled activation and aggregation of platelets play a crucial role in thrombotic disorders. Thus antiplatelet aggregating agents have therapeutic implications ,29,30,31NCB-NPs did not induce hemolysis of the RBCs. Thus, these are devoid of hemolytic activity. The non-hemolytic property indicates the biocompatibility property of the NPs.(1−x)CuxMn2O4-Bio (NCB-NPs) were produced by using a co-precipitation route at ambient temperature. The synthesized NCB-NPs were characterized by using PXRD, SEM and Raman techniques. XRD characterization confirmed the cubic spinel structure for the synthesized NCB-NPs. The lattice parameter and the crystallite size of the samples was calculated to be 8.3–8.6 Å and 23–28 nm. A significant variation in the lattice parameter and crystallite size has confirmed the doping of copper into the nickel manganites’ structure. A morphological investigation using SEM showed a non-uniform agglomerated polygon and plate-like structure with an increasing size as the copper content increased. The Raman spectral investigation also helped to confirm the cubic spinel structure of NCB-NPs. These NCB-NPs interfered in the blood coagulation cascade showed an anticoagulation effect and also inhibited the platelet aggregation. The hemolytic activity in RBC cells did not show with these NCB-NPs, suggesting their non-toxic nature. In conclusion, this study demonstrated that NCB-NPs can be used in the field of biomedical applications, especially as antithrombotic agents.The copper-substituted nickel manganites Ni(1−x)CuxMn2O4 series  (NCB-NPs) were produced by less expensive and effective co-precipitation route (sol–gel). Stoichiometric ratios of AR grade precursors from Burgoyne & Burbridges Company, Mumbai, India  were taken without further purification for the preparation. The solution of precursors and ionized water was continuously added with liquid ammonia (NH3), with constant stirring until a pH of 7 was obtained. After precipitation and filtration, the wet paste was dried at room temperature for 24 h. Then the dry paste collected was uniformly grinded into a fine powder, with the help of a mortar and pestle. Lastly, the dry powder, using alumina crucible, was sintered at 600 °C in a muffle furnace for four hours to get a dark-colored end-product: nickel copper manganite.The Niλ = 1.5406 Å, Silicon Lithium PSD detector) . The morphology of the samples was determined by the images recorded on SEM .  The Raman spectra were obtained by using Horiba Jobin Vyon, Tokyo, Japan, Model Lab Ram HR from Central Instruments Facility, Indian Institute of Technology Guwahati, Guwahati, India. The flowchart of synthesis and characterizations of NCB-NPs are as shown in Study of X-ray diffraction of the developed samples was performed with the help of spectra recorded on a Bruker AXS D8 Advance instrument  was pre-incubated with different concentrations of NCB-NPs for 10 min at 37 °C. Coagulation time was noted down after the addition of 20 micro-liter of 0.25 M CaCl2 to the mixture, which was pre-incubated. The time taken for the formation of a visible clot was noted.The plasma coagulant assay was performed in accordance with the method of Quick . Human bg for 15 min to prepare PRP. Similarly, the blood remaining after removal of PRP was centrifuged at 1100× g for 15 min to prepare PPP and the platelet count of PRP was adjusted to 4 × 108/mL. The PRP maintained at 37 °C was used within 2 h for the accumulation process. Plastic wares or siliconized glassware were used for all of the abovementioned preparations.The preparation of human plasma, one with platelet-rich another with platelet-poor, was performed according to the method of Ardlie and Han . BrieflyA Dual-Channel CHRONO-LOG Aggregometer (Model 700), Havertown, PA, USA, was used to monitor platelet aggregation with continuous stirring at 1000 rpm. PRP (250 µL) was pre-incubated with different concentrations of NPs. The platelet aggregation was begun by adding agonists such as ADP and followed the aggregation for 6 min.Preparation of erythrocyte suspension: Blood from a healthy individual was collected and mixed with trisodium citrate (3.2%) in the proportion 1:9. The centrifugation of citrated blood was performed at 3000 rpm for 5 min. The supernatant was disposed and the pellet was cleaned three times with normal saline solution (0.9%). The cells were again immersed in normal saline to make a 2% erythrocyte suspension.In vitro hemolytic behavior was assayed according to the method of Shin . Differe


Escherichia coli. We present an alternative method for the rapid expression, purification, and antimicrobial evaluation of LL-37, that involves only one purification step. (2) Methods: A DNA construct of SmbP_LL-37 was transformed into E. coli BL21(DE3); after overnight expression, the protein was purified directly from the cell lysate using immobilized metal-affinity chromatography. SmbP_LL-37 was treated with Enterokinase to obtain the free LL-37 peptide. The antimicrobial activity of both SmbP_LL-37 and free LL-37 was determined using the colony forming unit assay method. (3) Results: SmbP_LL-37 was observed in the soluble fraction of the cell lysate; after purification with IMAC, protein gel electrophoresis, and analysis by ImageJ, it showed 90% purity. A total of 3.6 mg of SmbP_LL-37 was produced from one liter of cell culture. SmbP_LL-37 and free LL-37 both showed inhibition activity against Staphylococcus aureus and Escherichia coli. (4) Conclusions: The SmbP fusion protein is a valuable tool for producing biologically-active LL-37 peptide. The production method described here should be of interest for the expression and purification of additional cationic peptides, since it cuts the purification time considerably prior to determination of antimicrobial activity.(1) Background: The cathelicidin peptide LL-37 is a prominent molecule with many biological activities, including antimicrobial. Due to its importance, here, we describe the production of LL-37 tagged with SmbP, a relatively new carrier protein that improves the production of recombinant proteins and peptides in  Nitrosomonas europaea is an attractive fusion protein for production of recombinant proteins and peptides in Escherichia coli. It is a 9.9-kDa protein whose biological function is the expulsion of toxic metal ions from the cell [The small metal-binding protein SmbP isolated from the periplasm of the bacterium the cell . SmbP imthe cell ,3. AfterStaphylococcus aureus and Escherichia coli in its entirety. This feature makes SmbP an attractive carrier protein for the expression of antimicrobial peptides with the same action mechanism as Bin1b  [We have previously reported the production of biologically active proteins, such as the human growth hormone, and the antimicrobial peptides (AMPs) Bin1b and VpDef tagged with SmbP, with satisfactory yields and purities ,5,6. IntThe antimicrobial peptide LL-37 is of great interest due to its multiple biological activities, including antimicrobial , antibioEscherichia coli, using different fusion proteins such as thioredoxin (THX), glutathione S-transferase (GST), and the carbohydrate-binding module III (CBM3) [LL-37 has previously been expressed in I (CBM3) ,17,18,19Escherichia coli is one of the most exploited microorganisms for expression of recombinant AMPs, because it can produce significant quantities of recombinant peptides at low cost [E. coli as a host can be challenging due to the small size of AMPs, their toxicity to the host cell, and their susceptibility to degradation due to a low molecular weight and high cationic properties [E. coli, expression with fusion proteins is a common strategy. Nonetheless, the yields are usually low after tag removal due to their higher molecular weights than the ones from the peptides. Therefore, SmbP, having a 9.9-kDa size, should improve the final yield. low cost . Howeveroperties ,22. For E. coli. We anticipated this result, since a previous work done in our laboratory showed that target recombinant proteins or peptides are primarily found in the soluble fraction with minor or no formation of inclusion bodies [A small-scale expression was performed to evaluate LL-37 production using SmbP as a fusion partner. n bodies ,6,23.A larger scale expression and purification procedure was then done. Routinely, fusion proteins are cleaved and removed, because they interfere with the biological activity of the recombinant peptides. As mentioned above, from our previous work, SmbP fused to Bin1b did not completely abrogate its antimicrobial activity. Consequently, the complete SmbP_LL-37 protein was used for the antimicrobial assay. However, since we also wanted to test the activity of the free LL-37 peptide, SmbP_LL-37 was digested with Enterokinase overnight. We tested the free LL-37 antimicrobial activity without further purification, as a mixture with SmbP, the minimal Enterokinase used, and the remnants of SmbP_LL-37, expecting a higher activity from a free peptide no longer fused to SmbP. Previous results have demonstrated that SmbP has no antimicrobial activity by itself . As for Staphylococcus aureus and Escherichia coli to test the bactericidal activity of SmbP_LL-37 and free LL-37, as they are some of the most common pathogenic bacteria [E. coli (ATCC 25922) and S. aureus (ATCC 25923). SmbP_LL-37 reduced growth of E. coli to ~28% with practically the same effect against S. aureus (~29%), being the first time the antimicrobial activity of LL-37 is tested when it is still attached to a fusion protein. After tag cleavage, the antimicrobial activity of free LL-37 increased significantly, reaching ~64% for E. coli and ~69% for S. aureus. Kanamycin, used as the positive control, inhibits 100% of the population of both S. aureus and E. coli (data not shown) at the same concentration (50 μM).It is well-known that LL-37 has antimicrobial activity against many Gram-positive and Gram-negative bacteria. We selected bacteria ,26. As sE. coli. They all involve a more complex purification method than our technique, and a multistep purification process increases the time and costs and complicates the scaling-up process. Furthermore, to verify LL-37 antimicrobial activity, these fusion proteins had to be removed. Our method using SmbP therefore seems a more practical approach to screen the expression, purification, and activity of antimicrobial peptides.Different fusion tags such as GST , Small UE. coli and S. aureus, being slightly more effective against S. aureus. This result was expected as compared to previous studies where LL-37 was expressed recombinantly in E. coli. The full recombinant protein SmbP_LL-37 showed antimicrobial activity against both bacteria. Nevertheless, the inhibition percentage was considerably lower than the results obtained from the free peptide. We previously observed the same pattern with the Bin1b peptide, where SmbP_Bin1b showed 25% activity against S. aureus and around 60% for E. coli. As previously discussed for Bin1b, the small size of SmbP does not interfere with the ability of LL-37 to fully exert its antimicrobial activity [Using GST as a fusion protein to express LL-37 has a relatively simple purification process, but the final LL-37 produced was 0.3 mg/L. The inability of GST to produce a high amount of soluble LL-37 combined with its size drastically reduces its final yield . Using TWe developed an expression system capable of producing free LL-37 in a one-step purification process and facilitated the screening of antimicrobial activity. However, if a pure LL-37 peptide is required, further purification using size exclusion chromatography, HPLC, or a combination of both can be used to obtain a purity over 95% ,28.E. coli expression and synthesized by GenScript . The sequence was digested with NdeI and XhoI, and ligated into pET-30a. The construct contains an Enterokinase cleavage site between the fusion protein SmbP and the LL-37 peptide for tag separation. E. coli strain DH5α was used for general cloning procedures and DNA maintenance. All constructs used in this work were fully characterized by sequencing.DNA constructs. The pET30a vector was digested with NdeI and XhoI restriction enzymes. The DNA sequence that codifies for SmbP_LL-37 was codon-optimized for E. coli BL21(DE3)-competent cells. For small-scale expression experiments, a single colony was cultured at 37 °C and 200 rpm in 20 mL of LB broth supplemented with kanamycin (30 μg/mL). Once the OD600 reached 0.4–0.6, the protein expression was induced by adding 0.1-M IPTG to a final concentration of 0.1 mM. The culture was incubated for an additional 16 h at 37 °C. For 1-L expression, overnight cultures were used to inoculate LB–kanamycin in baffled flasks and incubated at 37 °C until the OD600 reached 0.4–0.6. IPTG was added to a final concentration of 0.1 mM, and again, the culture was incubated for 16 h at 37 °C.Protein expression. The expression plasmid pET30a_SmbP_LL-37 was transformed into g for 10 min at 4 °C. Recombinant SmbP_LL-37 was purified with IMAC using the ÄKTA Prime Plus FPLC system . The supernatant was loaded into a HisTrap FF 1-mL column charged with Ni(II) and previously equilibrated with a lysis buffer; after sample loading, the column was washed with more lysis buffer. SmbP_LL-37 was eluted using an imidazole gradient (up to 200 mM) in 40 column volumes. The fractions were analyzed by SDS-PAGE or Tricine SDS-PAGE, the purity of SmbP_LL-37 being determined using ImageJ software . Subsequently, the pooled fractions were dialyzed against the lysis buffer. After dialysis, 20 units of Enterokinase, his, and bovine  were used per milligram of SmbP_LL-37 for digestion in a 2-mL reaction volume for 16 h at room temperature. Protein concentrations were quantified using the Bradford reagent, with bovine serum albumin (BSA) as the standard.Protein purification. Cells from the 1-L culture were harvested by centrifugation at 4 °C. The pellets were resuspended in lysis buffer . The cells were disrupted using a bead beater and 0.1-mm glass beads for 8–10 cycles of 15 s, followed by intervals of 45 s for cooling. Cell debris from the lysate was removed by centrifugation at 24,500× Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922) using the colony-forming unit (CFU) assay method [6 CFU per mL in sterile PBS buffer . Recombinant SmbP_LL-37, free LL-37, kanamycin , or the control buffer  was added to the bacterial suspension, and the cells were incubated at 37 °C for 3 h with shaking. After a 1000-fold dilution with a sterile phosphate buffer, 0.1-mL aliquots were spread on LB agar plates and incubated for 16 h to allow full colony development. After incubation, individual colonies of bacteria were manually counted. The ratio of colonies counted to the number of colonies on a control plate was calculated and averaged over three independent experiments. The antibacterial activity was described as the percentage of the population that was inhibited after the incubation.Antimicrobial activity. The recombinant peptide was analyzed against y method . In brieS. aureus and E. coli. After cutting with Enterokinase, the free LL-37 peptide increased its antimicrobial activity, as expected. Here, we offer a strategy that can be generally applied to more cationic peptides to quickly screen their antimicrobial properties against a wide variety of bacteria.In summary, we have reported the expression and purification of the antimicrobial peptide LL-37 with the SmbP fusion system. This strategy enabled rapid production with only one purification step for SmbP_LL-37, which showed activity against


LINC00622 and LINC01711 result in gene expression changes associated with cellular and inflammatory responses, respectively. Since there are no lncRNA databases focused on fibroblasts and fibrosis, we built a web application, FibroDB, to further promote functional and mechanistic studies of fibrotic lncRNAs.Most long non-coding RNAs (lncRNAs) are expressed at lower levels than protein-coding genes and their expression is often restricted to specific cell types, certain time points during development, and various stress and disease conditions, respectively. To revisit this long-held concept, we focused on fibroblasts, a common cell type in various organs and tissues. Using fibroblasts and changes in their expression profiles during fibrosis as a model system, we show that the overall expression level of lncRNA genes is significantly lower than that of protein-coding genes. Furthermore, we identified lncRNA genes whose expression is upregulated during fibrosis. Using dermal fibroblasts as a model, we performed loss-of-function experiments and show that the knockdown of the lncRNAs  Fibroblasts are the most common cell type in the connective tissue and are found throughout the mammalian body ,2. They The use of RNA sequencing ) technology has identified a large number of non-protein-coding (ncRNA) genes. When the length of an ncRNA is longer than 200 nucleotides (nt), this transcript is categorized as a long non-coding RNA (lncRNA) ,17,18,19https://rnamedicine.shinyapps.io/FibroDB/.Due to the increased interest to study fibrosis, a number of RNA-seq data have been deposited in the public domain, such as the Gene Expression Omnibus (GEO) and ArrayExpress. Since most of the published RNA-seq data were analyzed for protein-coding genes but not lncRNAs, analysis of such published RNA-seq data will be a valuable approach to uncover lncRNAs associated with fibrosis. To address this question, we gathered several published RNA-seq data to perform detailed analyses of lncRNAs expressed in fibroblasts and during fibrosis. To facilitate the further search of lncRNAs in fibrosis, we built a web application, FibroDB: The heterogeneity of fibroblasts has been discussed for many years, and there are currently no cell surface markers that identify all types of fibroblasts . To examWhen the top 20 highly expressed protein-coding B and lncp < 0.05  ,32, fibrp < 0.05 . Of thesp < 0.05 B as in fp < 0.05 .DNM3OS (DNM3 opposite strand/antisense RNA), from this screening. However, detailed profiling of other lncRNA genes was not provided in this study [dT]/antisense UAGCUAUCGGAGAACAAGC[dT][dT]; and LINC01711 sense GUCUGGAGCCGUUUCUCUC[dT][dT]/antisense GAGAGAAACGGCUCCAGAC[dT][dT]. The control siRNA used was Mission Negative control SIC-002, confidential sequence (Sigma-Aldrich). Transient siRNA transfection  was carried out using RNAiMax  according to the manufacturer’s protocol. The samples were collected 72 h after the transfection of siRNAs for the isolation of total RNA.To silence the target lncRNAs, the following MISSION siRNAs (Sigma-Aldrich) were used: 2. Then, the media were changed with the growth medium above, which are designated as the control (unstimulated). To stimulate fibrosis, recombinant human TGF-β1 (HEK293 derived)  was added to the growth medium at the concentration of 5 ng/mL. In the case of siRNA-based knockdown, siRNA was added to the culture medium at the time of medium change. The samples were collected 24 h after the stimulation with TGF-β1 for immunostaining and isolation of total RNA.To induce fibrosis, cells were serum-starved for one day in MEM supplemented with 1% MEM Non-essential Amino Acid Solution , 1% L-Glutamine solution , and 1% Penicillin-Streptomycin  at 37 °C with 5% CO-DDCt using ribosomal protein lateral stalk subunit P0 (PRLP0) as an internal control. The primer pairs were designed using Primer3  [https://genome.ucsc.edu/cgi-bin/hgPcr, 24 December 2021) before extensive testing by the conventional RT-PCR reaction followed by running the PCR product on an agarose gel to examine for a single band of the expected size for each primer pair. The primer sequences are provided in The TRIzol Reagent  was used to isolate the total RNA from cells and purified following the manufacturer’s protocol. SuperScript IV VILO Master Mix with the ezDNase Enzyme  was used to digest the genomic DNA and reverse transcribe one μg of total RNA for each sample to synthesize the first-strand complementary DNA (cDNA). After reverse transcription, the first-strand cDNA was diluted with DNase/RNase-free water to the concentration of 1 ng/μL. A quantitative reverse transcription polymerase chain reaction (qRT-PCR) reaction was performed with 1 ng of cDNA template per reaction using PowerUp SYBR Green Master Mix  via the QuantStudio 6 Flex Real-Time PCR System (Thermo Fisher Scientific) with the annealing temperature at 60 °C. Relative fold expression was calculated by 2er 2021)  and in sCells were washed once with ice-cold phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde  in PBS for 10 min. After three washes with ice-cold PBS, cells were permeabilized with 0.1% Triton-X 100  in PBS for 5 min and washed once with 0.1% Triton-X 100 in PBS. The primary antibody was diluted in PBS with 30% Blocker BSA  and 0.1% Triton X-100. The incubation of the primary antibody was conducted at 4 °C for overnight. After three washes with 0.1% Triton-X 100 in PBS, the secondary antibody was diluted in 0.1% Triton-X 100 in PBS to stain at room temperature (RT) for one hour: Goat anti-Rabbit IgG (H + L) Cross-Adsorbed ReadyProbes Secondary Antibody, Alexa Fluor 488 . The stained cells were washed three times with 0.1% Triton-X 100 in PBS. To visualize the nuclei, DAPI  staining was performed at room temperature for 5 min. The antibodies used in this study are provided in Non-directional RNA-seq was performed at Novogene  using the NEB Next Ultra RNA Library Prep Kit for mRNA-seq library preparation followed by sequencing with the Illumina Novaseq 6000 platform with a PE150 sequencing strategy.https://github.com/rstudio/DT), containing differential gene expression results from the study selected by the user. Normalized expression values were plotted via the R packages, ggplot2 [The FibroDB web application is based on the R package, Shiny . The app ggplot2  and plot ggplot2 . The tabAt the Explore page, the Heatmap tab displays an expression heatmap plotted via the pheatmap function from the R package, ComplexHeatmap . PathwayThe processed datasets from this study are hosted on a public AWS S3 bucket. The Downloads page provides instructions and links to access these data along with verbose descriptions. The Documentation page provides instructions for the usage of the application, rendered as HTML via the R package, R Markdown . FibroDBhttps://github.com/Bishop-Laboratory/FibroDB.All code used to generate FibroDB is available in the GitHub repository: t-test was performed to calculate a p-value via Microsoft Excel.Data are presented as the mean ± S.E.M. unless otherwise indicated. Two-sample, two-tail, heteroscedastic Student’s There are many lncRNA databases currently available . Yet, al


No significant difference between the two groups was observed in clinical response to ICIs (p=0.668). Progression-free survival (PFS) seemed to be longer in patients with non-cold type than cold type (p=0.332). In patients with adenocarcinoma, the non-cold type showed longer PFS than the cold type (p=0.036). Also, there were more patients with PD-L1 negative in the cold type compared to the non-cold type (p=0.050). In immune profiling, the proportion of effector memory CD8 T-cells was higher in patients with cold type than with non-cold type (p=0.015), and the proportion of terminal effector CD8 T-cells was lower in patients with cold type than with non-cold type (p=0.005). This pilot study has shown the potential for differences in prognosis and immune status between patients with cold and non-cold types. Hopefully, it provides essential information and insight into NSCLC patients' characteristics from the perspective of syndrome differentiation. Further large-scale observational studies and intervention studies are required.The cold-heat syndrome type (ZHENG) is one of the essential elements of syndrome differentiation in East Asian Medicine. This pilot study aimed to explore the characteristics of non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs) based on the cold-heat syndrome type. Twenty NSCLC patients treated with ICI monotherapy were included in the study and completed the cold-heat syndrome differentiation questionnaire. Demographic and clinical characteristics of the included patients were obtained through electronic medical records. Additionally, blood samples of 10 patients were analyzed with cytokine level and immune profiling. Patients were divided into two groups of cold type ( Lung cancer is the leading cause of cancer death, and according to the 2018 global cancer statistics, it accounts for 18.4% of all cancer death . ProgresComplementary and alternative therapies including herbal medicine are used for patients with NSCLC to enhance effects of conventional cancer therapies and reduce adverse effects –11. WithAstragalus-containing herbal formulae combined with platinum-based chemotherapy for NSCLC, the addition of herbal formulae to chemotherapy was more effective when the herbal formulae were given based on the syndrome differentiation [Syndrome differentiation, also named as pattern identification and “ZHENG,” is the representative characteristic of traditional medicine in Asian countries, including traditional Chinese medicine (TCM), traditional Korean medicine (TKM), and Kampo medicine. Practitioners comprehensively obtain clinical information by observation, listening, questioning, and pulse analysis and make a clinical decision of appropriate individualized therapy based on the syndrome differentiation of individuals , 20. In ntiation . Syndromntiation . In anotntiation .For the fundamental information for further studies, we planned to explore the clinical characteristic and immune function based on the “ZHENG” in NSCLC patients treated with ICIs. Cold versus heat syndrome type differentiation is the important and essential element of syndrome differentiation in East Asian Medicine –27. AlsoThis study is a pilot study conducted in one hospital in Korea, including 20 patients with NSCLC undergoing monotherapy of ICIs. Inclusion criteria were as follows: (1) patients who diagnosis as stage IIIB or stage IV of NSCLC histologically or cytologically; (2) patients who are undergoing monotherapy of ICIs ; and (3) patients whose ECOG performance status was 0 to 2. Eligible patients who agreed to participate with written informed consent filled out the questionnaires about the syndrome differentiation. Demographic and clinical characteristics of the included patients were obtained by the electrical medical record. Of the total 20 patients, 10 patients with cold or non-cold type were selected, and the immune profiles of patients' blood samples were additionally analyzed. The protocol was approved by the Institutional Review Board of the Asan Medical Center .A cold-heat syndrome differentiation questionnaire based on usual symptoms was used to measure the score of cold type and heat type . The queBy the cold syndrome questionnaire, there were 9 patients with cold type, and 11 patients with non-cold type. In the case of heat syndrome differentiation, there were 5 patients with heat type, and 15 patients with non-heat type. The demographic, clinical, and tumor characteristics of patients were compared in patients with cold type and in patients with non-cold type, according to the total score of the cold syndrome questionnaire.γ), IL-1β, IL-4, IL-5, IL-8, IL-10, IL-12p70, IL-22, and tumor necrosis factor-alpha (TNFα) [γ, and TNFα are representative T helper 1 (Th1) cell-associated cytokines and IL-4, IL-5, IL-6, and IL-10 are T helper 2 (Th2) cell-related cytokines [Blood samples of 10 patients were additionally analyzed for measuring cytokines level and immune cell profiling. We selected 10 patients that could represent the cold type and non-cold type based on the cold-heat syndrome type differentiation questionnaire. Five patients representing the cold type were selected based on their high cold syndrome scores. Five patients representing the non-cold type were selected based on their low cold syndrome scores and heat syndrome scores. CorPlex™ Human cytokine panel  was used to measure the following cytokines in patients' blood: interferon-gamma (IFN-a (TNFα) , 30. Tenytokines . Also, aytokines . The proContinuous variables were presented as mean ± standard deviation, and categorical variables were presented as frequency (%). Comparing proportions between two groups was carried out by the chi-square test or Fisher's exact test. Comparing means between two groups was carried out by an independent t-test. The software used for all the statistical analyses was R version 4.0.4 .The scores of each item in the cold-heat syndrome differentiation questionnaire were entered into the cluster analysis, and the 20 patients were divided into two groups. Hierarchical clustering was done using the R package factoextra , 35. Aftn = 14) and squamous cell carcinoma (n = 6), and the characteristics of total patients and patients with adenocarcinoma were presented (p=0.141). Between non-cold type and cold type, difference in drug use was observed (p=0.047); atezolizumab was prescribed in 77.8% of patients in cold type, versus 27.3% in patients in non-cold type. Line of therapy was investigated, and a majority of patients in non-cold type applied ICIs as 2nd line therapy . There was no significant difference in clinical response between two groups . Progression-free survival seemed to be longer in patients with non-cold type  days), compared to that in patients with cold type  days), which was not statistically significant in total patients (p=0.332). In patients with adenocarcinoma, progression-free survival was longer in patients with non-cold type  than that in patients with cold type  days) (p=0.036).From 22 August to 11 November 2020, 20 patients were included and completed the questionnaire about cold-heat syndrome differentiation. Based on the score of the cold syndrome, 11 (55%) patients were non-cold type, and 9 (45%) patients were cold type. The histologic type of included patients was divided into adenocarcinoma (resented . Mean agp=0.050). In patients with adenocarcinoma, PD-L1 negative seemed to frequently appear in cold type compared to non-cold type, which was not statistically significant (p=0.110). Proportion of mutated EGFR seemed to be higher in patients with cold type than in patients with non-cold type, although the difference between the two was not statistically significant (p=0.115). There was no difference observed between the two groups in ALK and KRAS status.PD-L1 status was evaluated by SP263  and 22CS  ,38 in alp=0.208, p=0.208, respectively). In immune profiling, which was calculated as percent by intact live cells, effector memory CD8 T-cells were 3.8 ± 0.8% in patients with non-cold type and 6.2 ± 1.6% in patients with cold type (p=0.015). Also, terminal effector CD8 T-cells were 13.2 ± 1.9% in patients with non-cold type and 7.9 ± 2.4% in patients with cold type (p=0.005)  . In the n = 15) and group B (n = 5) . It seems that there are more patients with PD-L1 expression higher than 50% in group A, compared to group B (p=0.051). Radar charts of the mean standardized score of each symptom , in the two cluster groups are shown in By hierarchical clustering using the score of symptoms in the cold-heat syndrome differentiation questionnaire, 20 patients were divided into group A ( (n = 5) . All patIn this pilot study, tumor-related characteristics and immune profiles of NSCLC patients treated with ICI monotherapy, depending on cold-heat syndrome type differentiation, were examined. According to the cold syndrome questionnaire, patients were divided into the cold type group and non-cold type group. Though the clinical response to ICI monotherapy was not different between the two groups, the progression-free survival periods seem to be longer in the non-cold type group than in the cold type group. Also, PD-L1 negative patients seem to be frequently observed in the cold type group, compared to the non-cold type group. In immune profiling, patients with cold type showed a higher proportion of effector memory CD8 T-cells and lower terminal effector CD8 T-cells than patients with non-cold type.Patients were divided into the cold type or non-cold type according to the score of the cold syndrome questionnaire. By the questionnaire of cold-heat syndrome differentiation, patients can be divided into four types: no cold-heat, cold, heat, and cold-heat complex . Of the There were more patients with PD-L1 negative in the cold type group compared to the non-cold type group. PD-L1 expression is one of the representative biomarkers for anti-PD-L1 or anti-PD-1 therapy . In a clMeanwhile, patients with cold type showed a higher proportion of effector memory CD8 T-cells and lower terminal effector CD8 T-cells, compared to patients with non-cold type. ICI therapy enhances the effector function of T-cells by the restoration of the activity of exhausted CD8 effector . CirculaCluster analysis using the score of each item in the cold-heat syndrome differentiation questionnaire was additionally conducted. Both items in cold syndrome and heat syndrome were included for the analysis. Patients in one group showed higher scores in heat syndrome symptoms, whereas patients in the other group showed higher scores in cold syndrome symptoms. The difference in symptoms of “intolerance to cold” was commonly observed by the cluster analysis of this pilot study and a previous study . The sigTo the best of our knowledge, this pilot study is the first study to investigate the clinical response and immune status of NSCLC patients treated with ICI monotherapy from the perspective of cold-heat syndrome differentiation. Hopefully, the results of this pilot study will provide essential information about the characteristics of NSCLC patients from the standpoint of syndrome differentiation in East Asian medicine. Also, there are several limitations to our study. First, the sample size of this study was relatively small. The aim of this pilot study was to obtain basic data for future research studies. Large-scale further research studies are needed to reach clinically and statistically meaningful conclusions. Second, we used the cold syndrome questionnaire's cutoff score, which was developed in a healthy population. Third, there were only three female patients in our study, and all female patients were included in the cold type group. Some differences between cold type and non-cold type groups were observed, but we could not exclude the possibility that they were caused by gender differences. In a previous study of cold and non-cold types, 38.1% of males and 61.9% of females corresponded to cold type, and 59.4% of males and 30.6% of females corresponded to non-cold type . It seemThis pilot study has shown the potential differences in prognosis and immune status between patients with cold type and non-cold type. From the result of the study, NSCLC patients with cold type seem to present shorter progression-free survival and to have a low level of PD-L1 expression, compared to patients with non-cold type. Also, the proportions of effector memory and terminal effector CD8 T-cells were different between the two groups. When planning a clinical trial of combining herbal medicine and ICIs, the fundamental clinical information from our pilot study will hopefully provide useful insights into the patients' characteristics regarding cold-heat syndrome type (ZHENG). Further large-scale observational studies and intervention studies are required.


MD-PhD trainees constitute an important source of physician-scientists. Persistence on this challenging path is facilitated by success in garnering independent (R grant) support from the NIH. Published research tracks academic appointments and global R01 success for MD-PhD trainees but has not included information on future funding success of individual MD-PhD predoctoral grant holders. Here, we used data from the NIH RePORTER database to identify and track the funding trajectory of physician-scientists who received predoctoral grant support through the F30 mechanism, which is specific for dual-degree candidates. Male and female F30 awardees did not differ in their success in garnering K  grants, but, among F30 grant awardees, men were 2.6 times more likely than women to receive R funding. These results underscore the need for analysis of factors that contribute to the disproportionate loss of NIH-supported female physician-scientists between the predoctoral F30 and the independent R grant–supported stages.  Physician-scientists have been a cornerstone of academic medicine and science and have pioneered basic, translational, and clinical discoveries to benefit patients’ lives. The concept of physician-scientists has been championed since the 1950s, beginning with the tenure of James Shannon, MD, as NIH Director. Many physicians engaged in research at NIH as an option to meet obligations of the physician draft from the Korean to the Vietnam War , 3. SincHowever, as soon as the late 1970s, leaders in medicine voiced concerns about physician-scientists as an “endangered species” . With thhttps://reporter.nih.gov/) to follow MD-PhD trainees, starting with the F30 NRSA fellowship award. It is conceivable that predoctoral F30 grant MD-PhD awardees, having demonstrated early competency to garner funding, will be better prepared to compete for future funding and to persist in academic careers independent of gender. We specifically focused on this group of dual-degree physician-scientists and subsequently analyzed the proportions and time to award for those who go on to receive K and R support, with analysis of gender differences at each of these time points.Knowledge gaps remain about the dynamics of attrition along the physician-scientist training pipeline –15. MoreWe captured data on awardees receiving F30 awards between 1990 and 2012 . Over thWe observed that the majority of F30 awards were granted in the past 10 years, many of which were beyond our K or R capture period due to the fact that we wanted to allow for adequate follow-up time . OverallP = 0.29, Fisher’s exact testing).F30 grantees who received their award between 1990 and 2012 were included in the F30-to-K analysis. Over this time period, there were 1015 F30 awardees, 404 (39.8%) of whom were women and 611 (60.2%) of whom were men. With a subsequent median follow-up period of 11.9 years for these F30 awardees, we found that 159 (15.7%) of the F30 awardees went on to receive a K-equivalent award, including 57 women (35.8% of K recipients) and 102 men (64.2%). With normalization, 14.1% of women who received an F30 award went on to receive a K award ; 16.7% of men who received an F30 award went on to receive a K award (102 of 611 eligible)   . In the testing) .P = 0.41, Fisher’s exact testing). Of these 101 K awardees, 48 went on to receive an R award, indicating a K-to-R conversion of 47.5% .F30 grantees awarded between 1990 and 2007 were included in the F30-to-R analysis. Over this time period, there were 433 F30 awardees, 162 (37.4%) of whom were women and 271 (62.6%) of whom were men. For this cohort, with a subsequent median follow-up period of 16.6 years from the start of F30 funding, we found that 101 (23.3%) proceeded to receive a K award, with a median time to start of the K award at 11.0 years. The success of women  and men  receiving K awards within this R cohort was comparable .Independent of the K award mechanism, an additional 32 individuals who had F30 awards went on to receive R awards, bringing the total F30-to-R conversion rate to 18.5% (80 of 433). The F30-to-R award recipients included 15 women (18.8%) and 65 men (71.2%). With normalization, 9.3% of women who received an F30 award went on to receive an R award (15 of 162); 24.0% of men who received an F30 award went on to receive an R award (65 of 271)   . In the testing) .P = 0.19) (P = 0.77)  . For R r = 0.77) .While F30 recipients’ overall success rate in obtaining K awards was lower than we expected, we found a 48% increase in the proportion of K grant success (23.3% vs. 15.7%) in the cohort followed for a median of 14.2 years versus those followed for 10.7 years, suggesting that the length of the training period for physician-scientists delays achievement of this milestone. The rates of K awards for MD-PhD F30 recipients are comparable to or exceed those reported elsewhere for MD-PhDs . Rates oWe could not identify literature analyzing future NIH funding for PhD-only predoctoral NIH grantees to compare with that of the MD-PhD cohort. In order to estimate this, we analyzed K and R funding for individuals receiving F31 awards over the same periods of time that we analyzed for MD-PhD trainees receiving F30 funding. F31 grants are predoctoral NRSA grants that fund graduate work only, unlike F30 awards, which are restricted to dual-degree candidates and fund both graduate and medical school stipends. As such, the large majority of MD-PhD trainees use the F30 rather than F31 mechanism, save for those applying to institutes  that do not participate in the F30 award mechanism. While some MD-PhDs are therefore included in the F31 pool, the great majority of F31 awardees are PhD-only trainees. Given the larger number of PhD trainees, 14 times more F31 grants than F30 grants were awarded in 1990–2007, and roughly 12 times more F31 than F30 grants were awarded in 1990–2007. Given the challenge of manually curating this larger grant portfolio, we report only total numbers and not a gender breakdown for future grants for the F31 cohort (see Methods).Compared with future grants received by F30 recipients, we observed a much smaller percentage of F31 recipients receiving K awards but a larger proportion receiving R awards .These data may overestimate the number of K and R awards obtained by the PhD-only cohort, given the inability to remove MD-PhD F31 recipients from the pool .A central feature in the training of MD-PhD candidates is the development of skills in planning and writing compelling predoctoral grants to the NIH to be funded under the Ruth Kirschstein NRSA F30 mechanism. Garnering F30 support reflects a mastery of scientific thinking and communication, because successful proposals require demonstration of strong foundational knowledge in the area of the proposed project and framing of rigorous investigative plans. The current study captured all MD-PhD F30 awardees from 1990 to 2012 and tracked individual-level funding trajectories to uncover trainee-specific and time-dependent award histories. We expected that the subset of MD-PhDs who had demonstrated ability to earn extramural funding early in their training could be expected to parlay this experience at later points in their career.We utilized the F30 funding mechanism to identify dual-degree MD-PhD trainees for this study. From this cohort, a minority of F30 awardees went on to obtain K award (15.7%) or R award (18.5%) funding, with median follow-up of 10.7 and 14.2 years, respectively. This indicates that while F30 funding may benefit future success in procuring grants, it is insufficient for garnering K- and R-level grant support from NIH. Whether F30 funding increased the success rate of future R01 submissions cannot be judged, because data on total applications by MD-PhD trainees were not accessible to us. We can conclude, even for this elite cohort of predoctoral physician-scientist F30 awardees, that gender disparity manifests at the level of independent funding. Men and women obtained (mentored) K grant funding at equal rates; however, the success of women in obtaining independent R grant funding was only 40% of that of their counterparts who were men. For those F30 awardees who did get a K award, the subsequent conversion rate to an R award was 47.5%; the conversion rate showed a substantial gap between the genders (29% K-to-R conversion rate for women compared with a 56% conversion rate for men).These findings bring about questions of whether F30 grants help to train the next generation of physician-scientists. Two issues are worth noting. First, R01 success may be an inadequate measure of the value of successful predoctoral grant preparation and submission. A large proportion of MD-PhD program graduates support their research with foundation and/or pharmaceutical company money rather than NIH grants, as noted in Brass and Akabas .Notably, physician-scientist training allows trainees to garner skills that are attractive for several career paths and clinical/translational contributions independent of the RPG measure. The scope of activities in which physicians contribute to discovery is broad and increasing.Second, the years captured in our study could underestimate the linkage between F30 receipt and future funding. The majority of F30 grants were awarded after the window considered in this study, and the overall effect of F30 receipt on independent grant acquisition is not yet evident for most recipients. Our cohort also preceded the broad implementation of K99/00 and similar transitional funding mechanisms. Even for those captured in this study, the follow-up period may be inadequate given the extended training required of physician-scientists currently and the effect of clinical commitments on the pace of productivity. Curriculum vitae analysis would help determine whether F30 recipients move from academic medicine into other careers.Almost half of those who did receive an R award, in this F30 cohort, did not receive an antecedent K award. Multiple factors could contribute to this finding, including a decision by MD-PhDs to forego this opportunity in order to limit training duration, institutional pressure to forego the smaller grant , or less emphasis on the K award in the earlier MD-PhD cohort that we targeted for R award analysis. For a subset of F30 awardees, pursuit of a K award may be perceived as too costly an extension of the training period. The need to shorten training time was noted as one of the main action items by the 2014 Physician-Scientist Workforce Working Group. This group suggested shortening the time to independent research by 5 years .K awards were rarer among the primarily PhD-only recipients of predoctoral F31 training grants. This likely reflects the limited use of K awards by the NIH for PhD scientists (whereas the K08 and K23 mechanisms are limited to clinicians), as well as the fact that the major K award used, the K99, was introduced late in the capture period. Notably, the percentage of R awards was higher in the F31 recipient pool . This could be a manifestation of the higher reliance on independent R awards early in the academic PhD career and/or a shorter training period compared with MD-PhDs. While beyond the scope of this study, it is conceivable that receipt of F31 grants by PhD trainees tracks with persistence in academic careers.Our finding of a funding discrepancy between male and female MD-PhDs occurring during the K-to-R transition is not without precedent. Previous work into the funding rates of physician-researchers with K awards showed significantly lower R01 funding rates for women compared with men , 9, and Discrimination against women in science fields has been well documented and is relevant to female grantees in our MD-PhD cohort. Reports in the 1990s and early 2000s described the overt discrimination against women with equal qualifications to colleagues who were men. To address the reason for the disparity in women attaining funding and senior faculty positions at academic institutions that we continue to see today, Ceci and Williams analyzed discrimination against women in journal reviews, grant funding, and hiring in math-intensive and science fields . The autThe process of generating a successful predoctoral NIH grant acquaints MD-PhD trainees with the mechanics and critical thinking involved in future grant submissions but is insufficient preparation on its own for future independent NIH funding. Moreover, the inability to procure R-level funding contributes to attrition in the physician-scientist pipeline. Persistence requires both extrinsic progress  and intrinsic career factors  , 27.Contributory barriers to persistence and funding success as a physician-scientist include difficulty in balancing clinical and research responsibilities and professional and personal life needs –31. At oA better understanding of attrition in grant acquisition by those receiving predoctoral NIH support can illuminate whether the leakiness in the physician-scientist pipeline reflects informed syntonic choices or disruption of careers by funding gaps. Steps to sustain physician researchers extend beyond scientific and professional development skills. Among faculty, time-banking interventions to offset work-work and work-life time conflicts have been reported to yield sizable benefits . Career Our individual-level data were obtained from public funding records, and information at that level on application rates for K and R awards was not available to us. This limits our ability to convincingly parse contributory factors to the observed overall and gender-specific award rates. An additional limitation was that the distribution of F30 awards was left skewed in our data set. While the first F30 was awarded in 1990, the majority of F30 awards have been awarded beyond 2010. Therefore, our analysis here captures the first generation of dual-degree physician-scientists who received funding through this mechanism but does not capture the majority of those who have received this award. Subsequent analyses must be performed to verify whether the trends seen here persist through the current generation of early career physician-scientists who are applying for K or R awards. Additionally, a subset of early F30 awardees (1990–2007 cohort) will continue to obtain their first R grants after the cutoff set for analysis in this paper.With ongoing first R funding for this group, it is premature at this point to conduct definitive qualitative analysis of characteristics  associated with delayed first R grant acquisition.Since their conception in the 1950s, there has been substantial growth in the numbers of MD-PhD programs. As of 2016, there are 90 MD-PhD programs, 45 of which are funded by the NIH through MSTP (T32) awards (F30 recipients were identified through the NIH’s Research Portfolio Online Reporting Tools (RePORT). F30 data were downloaded for each year from 1990 through the end of 2019 (data was accessed in December 2020). Each year’s F30 grantees were collated into a single data file. We focused specifically on MD-PhD dual-degree predoctoral grantees and removed DVM/PhD, DDS/PhD, and AuD/PhD F30 recipients from the analysis. Additionally, because F30 grants span multiple years, grantees are listed in RePORTER for each year of funding. We therefore removed duplicate entries and only kept the individual grantee entry that corresponded with the start of their F30 grant.To determine if and when F30 recipients advanced to receive K- or R-level NIH awards, we manually searched each F30 recipient on NIH RePORTER to determine (a) if they received a K- or R-level award, (b) the specific type of K or R award and their equivalents, and (c) the time to award, calculated as the start of the F30 award to the start of the K and/or R award. K awards and equivalents included the following award mechanisms: K01, K02, K08, K22, K23, K38, and K99. R awards and equivalents included the following award mechanisms: R01, R03, R21, R34, R35, R43, and R56, with the R01 mechanism constituting the majority (70%) of awards. When we allude to K or R awards, we are including all of these mechanisms. The follow-up period lasted from the start of the F30 grant to either the start of the K or R award or until the date of final data collection .As gender was an important variable in this analysis, two authors independently conducted internet searches to attribute gender for the F30 recipients on the basis of text from institutional websites, use of gender-specific pronouns, or an explicit statement of gender, which is consistent with methods used by prior publications , 9. In nWe also analyzed the success of F31 grant awardees (primarily PhD-only candidate programs) in obtaining future NIH K or R funding. The pool of F31 awardees is over 10 times greater than that of F30 recipients, making manual curation impractical. We used the RePORTER database functionality rather than manually curating the grant trajectory of F31 awardees. Those receiving F31 grants between 1990 and 2007 and between 1990 and 2012 were identified through searching RePORTER, and their PI IDs were collected and used to search all associated awards for each cohort up to 2021. Awards were filtered for unique listings  to remove multiple award listings from successive years. Manual curation of a subset (1100) of results showed that 1.9% of PIs were assigned multiple PI IDs . Additionally, awarded grant results contained co-PIs who had not received a prior F grant (8.9% of unique PI listings). We considered double ID listings and co-PI listings to constitute false positives and reduced the level of K awards ascribed to the entire F31 cohort by 1.9% and that of R awards (in which co-PI’s appear) by 10.8% (1.9% + 8.9%). Applying this search strategy to our F30 cohort gave results consistent with the manual F30 search.To account for differences in time to grant receipt, we analyzed K and R awards in the following manner. For the F30-to-K award analysis, we analyzed all individuals who received an F30 award between 1990 and 2012. For F30-to-R award analysis, we analyzed all individuals who received an F30 award between 1990 and 2007 (summarized in P values of less than 0.05 were considered significant.We analyzed the data using Stata v.15. We used Fisher’s exact test to determine if proportional differences existed between men and women who received K and R awards. We used the Kaplan-Meier method to estimate the probability of the receipt of K and R awards and the log-rank test to assess differences between men and women. Receiving a K or R award through May 2021 was considered the event of interest for F30 recipients. Displayed bars in figures represent the median with 95% CI. This retrospective cohort study was exempt from institutional review board approval, as all data are publicly available.CRK, NC, SGC, and RAS designed the study. NC acquired the data. NC, RAS, SGC, and SMN performed data analysis and determined statistical plan. CRK, NC, RAS, and SGC drafted the manuscript. CRK, NC, RAS, SGC, and SMN provided critical revision of the manuscript.